AB0532 LACTATE DEHYDROGENASE AS A PREDICTOR OF FATIGUE IN PRIMARY SJOGREN’S SYNDROME:A POOLED ANALYSIS
Authors: L. Rajagopala, S. Jude Tan, W. F. Ng, J. Tarn
Journal: Annals of the Rheumatic Diseases (2022)

Background Fatigue is one of the most disabling symptoms in primary Sjogren’s syndrome (pSS) and it significantly impacts patient’s quality of life[1]. However, the cause of this symptom remains unclear. Lactate dehydrogenase (LDH), is an enzyme of the anaerobic respiratory pathway. High lactate levels are a marker of inflammation and create a pro-inflammatory microenvironment[2]. LDH levels can be raised in myositis, haemolysis and lymphoma. For this reason, serum LDH is routinely monitored in patients with pSS. However given its role in metabolic pathways, we hypothesize that serum levels of LDH may also be a biomarker of fatigue in pSS. Objectives 1. To investigate the bivariate relationship between LDH and fatigue severity, hypothesizing a positive correlation between them. 2. To incorporate factors such as depression, anxiety, serum creatinine and haemoglobin levels as covariates, as these factors may also contribute to fatigue Methods We used routinely collected clinical and laboratory data from 512 pSS patients from the Newcastle Sjogren’s syndrome cohort. The participants consented for their linked anonymised data to be used in pSS-related research. Severity of fatigue was measured using fatigue subscale of EULAR Sjogren’s Syndrome Reported Patient Index (ESSPRI)– a Likert scale of 0-10. Fatigue severity was also categorised into 4 categories: 0-2 being minimal, 3-5 mild, 6-7 moderate and 8-10 severe. Hospital Anxiety and Depression Score was used to measure patients’ anxiety and depression levels. Blood parameters including haemoglobin, full blood count, ESR, CRP, serum creatinine, alanine aminotransferase (ALT), alkaline phosphatase (ALP) and LDH were checked during each visit. Dryness was measured using ESSPRI dryness subscale.Statistical analysis of the relationship between the continuous blood parameters and categorical fatigue groups was performed using Kruskal-Wallis for categorical fatigue groups and linear regression for continuous fatigue measures. Results The majority of the patients were female (87%) and Caucasian. Baseline measurements of pain, anxiety, depression, abnormal fatigue, mental fatigue and overall ESSPRI score increased with increasing fatigue severity.This is seen most prominently in serum LDH levels. LDH levels increased with increasing fatigue scores. We identified significant differences in baseline LDH levels across the four fatigue groups (p = 0.002). Within groups comparisons showed significant differences between mild and minimal, severe and minimal and moderate and minimal fatigue groups only (p-values: 0.026, 0.019 and 0.032 respectively). A baseline linear regression model for fatigue using LDH, CPK, age and gender was performed and showed LDH has a significant relationship with fatigue p=0.007.Findings were also determined using ANOVA where significant difference (p= 0.0023) of LDH between fatigue groups were identified using Kruskal-Walis test. A supplementary Tukey-Kramer test was carried out to determine if LDH was significant between two-groups of fatigue severity score, where significant difference was seen between three different sets of fatigue categories: mild-minimal, severe-minimal and moderate-minimal. The test ensured that a relationship between the enzyme and fatigue was present especially between the groups of fatigue severity stated above.The actual-by-predicted and leverage plot further supporting our findings by showing the unique effect of LDH in the models. Conclusion The study concludes that a relationship between enzyme lactate dehydrogenase and fatigue exist; however, further study will be required to examine its role as a predictor of fatigue severity in pSS. The complex interconnection between inflammation, disease activity, psychological factors and LDH will have to be further investigated to advance the current understanding of chronic fatigue in Sjogrens syndrome. References [1]Fatigue and immune activity in sjogren’s syndrome [2]Lactate at the crossroad of metabolism, inflammation, and autoimmunity Disclosure of Interests None declared